The Influence of AI-Powered Personalized Advertising on Consumer Purchase Intention: The Mediating Role of Brand Trust in Pakistan’s E-Commerce Sector

Abstract

AI has helped e-commerce companies to create highly personalized ads, but it is still unknown if personalized advertising can lead to purchase intent in emerging markets. In this research, the effect of personalized ads using AI on purchase intention was assessed and brand trust was tested as mediator in the e-commerce market of Pakistan. The data collection process was based on a cross-sectional design and 280 online active consumers were selected using purposive sampling, where a new five-point Likert Scale questionnaire was used to measure the advertising personalization, perceived relevance, brand trust, and intent to purchase. Data were screened and described in SPSS and the hypothesized relationships were tested using partial least squares structural equation modelling (PLS-SEM) in SmartPLS 4 with bootstrapping using 5000 resamples. The measurement model was found to be reliable and valid. Personalization of the advertisement and perceived relevance had significant direct effects on purchase intention (β = .16 and .20, respectively) and both advertising constructs predicted brand trust (β = .28 and .45, respectively). In turn, brand trust was the strongest predictor (β = .45) and partially mediated the impact of both the personalization of the advertising and the perceived relevance of advertising. The model accounted for 50% of the variance in purchase intention. The results show that the personalization is not enough: relevance has to be translated into trust in order to be of commercial value to advertisers.